Systems and methods for multi-resource scheduling

ABSTRACT

Systems and methods are provided to schedule clinical tasks involving multiple sub-tasks and multiple resources in a clinical enterprise. An example method includes identifying a slot for a task defined by a task duration and one or more resources, the task including a plurality of sub-tasks, each sub-task having a sub-task duration utilizing one or more of the one or more resources, wherein each sub-task to be performed consecutively based on resource constraints; selecting a time slot for the task based on resource availability, the plurality of sub-tasks in the task, and a duration associated with each sub-task, wherein resource availability information is obtained from a clinical information system, and wherein each resource is scheduled only for one or more sub-tasks in which the resource is involved; displaying the schedule including the task and the plurality of sub-tasks; and facilitating access to view and modify the schedule.

CROSS-REFERENCE TO RELATED APPLICATIONS

The present application claims the benefit of priority to U.S.Provisional Patent Application No. 61/264,551, filed on Nov. 25, 2009,entitled “SYSTEMS AND METHODS FOR MULTI-RESOURCE SCHEDULING”, which isherein incorporated by reference in its entirety.

FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT

Not Applicable

MICROFICHE/COPYRIGHT REFERENCE

Not Applicable

BACKGROUND

The invention relates generally to process management systems, and moreparticularly to scheduling systems in the clinical setting, such ashealthcare delivery institutions or hospitals.

Healthcare delivery institutions are business systems that can bedesigned and operated to achieve their stated missions robustly. As isthe case with other business systems such as those designed to provideservices and manufactured goods, there are benefits to managingvariation such that the stake-holders within these business systems canfocus more fully on the value added core processes that achieve thestated mission and less on activity responding to variations such asemergency procedures, regular medical interventions, delays,accelerations, backups, underutilized assets, unplanned overtime bystaff and stock outs of material, equipment, people and space that areimpacted in the course of delivering healthcare.

Currently clinical process decisions have historically relied on the artof understanding symptoms and diagnosing causality much in alignmentwith the practice of the medical diagnosis arts. In an ever-evolvingenvironment, judgment and experientially-developed mental models areutilized by the healthcare providers to utilize the informationcurrently at hand to make decisions. Presented with similar data, thedecision made from one caregiver to another typically exhibits avariation. Presented with partial information, which is the byproduct ofbeing organized in functional departments, specialties, roles and by thenature of having partial and/or current or dated informationavailability on hand—clinical process decisions vary widely andtypically are locally focused for lack of a systems view upstream anddownstream of the decision point.

As a hospital processes care plans on an increasing patient load, thesevariations in medical condition and selected treatment plans perturbsthe schedules of doctors, nurses and assets such as rooms and equipment.If there is protective capacity in these schedules and staff, theproviders of care can manage variation while maintaining care quality.When randomness and interdependencies exceed the ability to serve, careproviders are forced to make choices amongst poor alternative options;someone or something is going to be bottlenecked or overextended.Delays, queues, overtime, burnout and emotional decision makingcharacterize systems that are over-taxed or beyond their ability toperform.

Where information systems exist, they are simply informational innature. Examples include scheduled rooms, people, materials andequipment. Recent advances in locating devices such as those utilizingradio-frequency identification (RFID) technology to report a location ofa tagged asset are utilized, yet personnel are loath to be tracked bywearing a device. RFID devices are not pervasive, and the systems thatmonitor them are not fully integrated with the requisite adjacentsystems that gather contextual information. The current art is notpredictive, probabilistic nor necessarily systemic. For example, knowingthe location of an asset is desirable but knowing its anticipated needand interdependencies is required to make a decision to use a locatedasset actionable. The information required for such a decision comesfrom a plurality of adjacent health information systems and must have anability to play forward into the future.

Today, current procedure duration and room status is provided withoutany proactive or forward-looking capability. Schedules are producedbefore a day's activities commence. Process status is displayed alongwith trending and, often, alarm functionality should a process variabletrip a threshold set point. Today, processes are planned for a givenvolume; when that volume is exceeded or processes have sufficientvariation to overtax their capability, scheduling and recovery arereduced to manual triage and experience to sort out. Typically, queues,delay, overtime and cancellation result; there is no proactive decisionsupport to dynamically reschedule people or physical assets or supplies.

Radiology Information Systems (RIS) and other clinical informationsystems are in wide use in the healthcare industry to manage radiologydepartments in hospitals and independent radiology clinics. Thesesystems typically incorporate functionality to schedule patients onradiology equipment such as computed tomography (CT) and magneticresonance imaging (MRI) machines. However, radiology exams also requirea numbers of other resources such as technicians, nurses, radiologists,anesthesiologists and other equipment such as portable ultra sound andX-ray machines. In general, these resources are not scheduled and areassumed to be available during the times when the exams are scheduled.However, this is not always true and leads to delays in completing thescheduled exams.

BRIEF SUMMARY

Certain examples systems and methods for multi-resource scheduling toschedule resources involved in an exam. Certain examples enable bothautomatic and manual scheduling and/or rescheduling of inpatient andoutpatient appointments.

Certain examples provide a multi-resource scheduler system for aclinical enterprise. The system includes a processor connected to amemory, wherein the processor is programmed to implement the system. Ascheduler engine is to generate a schedule for a clinical facilityinvolving multiple tasks and using multiple resources. The schedulerengine is to identify a slot for a task defined by a scheduled taskduration and one or more resources. The task includes a plurality ofsub-tasks, and each sub-task has a sub-task duration utilizing one ormore of the one or more resources. Each sub-task is to be performedconsecutively based on resource constraints. The scheduler engine is toidentify and select a time slot for the task based on resourceavailability, the plurality of sub-tasks in the task, and a durationassociated with each sub-task. Resource availability information isobtained from a clinical information system. Each resource is scheduledonly for one or more sub-tasks in which the resource is involved. Ascheduler interface is to display and facilitate access to the scheduleincluding the task and the plurality of sub-tasks.

Certain examples provide a tangible computer-readable storage mediumincluding a set of instructions for execution on a computer. The set ofinstructions, when executed, implementing a multi-resource clinicalscheduler. The scheduler includes a scheduler engine to generate aschedule for a clinical facility involving multiple tasks and usingmultiple resources. The scheduler engine is to identify a slot for atask defined by a scheduled task duration and one or more resources. Thetask includes a plurality of sub-tasks. Each sub-task has a sub-taskduration utilizing one or more of the one or more resources. Eachsub-task is to be performed consecutively based on resource constraints.The scheduler engine is to identify and select a time slot for the taskbased on resource availability, the plurality of sub-tasks in the task,and a duration associated with each sub-task. Resource availabilityinformation is obtained from a clinical information system. Eachresource is scheduled only for one or more sub-tasks in which theresource is involved. The system includes a scheduler interface todisplay and facilitate access to the schedule including the task and theplurality of sub-tasks.

Certain examples provide a computer-implemented method for scheduling ofclinical tasks involving multiple sub-tasks and multiple resources in aclinical enterprise. The method includes identifying a slot for a taskdefined by a task duration and one or more resources, the task includinga plurality of sub-tasks, each sub-task having a sub-task durationutilizing one or more of the one or more resources, wherein eachsub-task to be performed consecutively based on resource constraints;selecting a time slot for the task based on resource availability, theplurality of sub-tasks in the task, and a duration associated with eachsub-task, wherein resource availability information is obtained from aclinical information system, and wherein each resource is scheduled onlyfor one or more sub-tasks in which the resource is involved; displayingthe schedule including the task and the plurality of sub-tasks; andfacilitating access to view and modify the schedule.

BRIEF DESCRIPTION OF SEVERAL VIEWS OF THE DRAWINGS

FIG. 1 is a block diagram illustration of an example system to planclinical procedures.

FIG. 2 illustrates an example of patients scheduled by day in radiologydepartments.

FIG. 3 depicts an example of clinical tasks and resources within ascheduled duration.

FIG. 4 shows example clinical tasks and resources within a scheduledduration.

FIG. 5 illustrates an example of resource constraint and routing.

FIG. 6 illustrates an example resource utilization analysis.

FIG. 7 depicts an example heuristic algorithm for sorting time slotsbased on desirability and presenting results to a user who is schedulingan exam.

FIG. 8 describes an example methodology for rescheduling exams toaccommodate an emergency exam.

FIG. 9 is a block diagram illustration of an example multi-resourcescheduling system for use in planning clinical procedures in a clinicalenterprise.

FIG. 10 is a schematic diagram of an example processor platform that maybe used and/or programmed to implement the example systems and methodsdescribed herein.

The foregoing summary, as well as the following detailed description ofcertain embodiments of the present invention, will be better understoodwhen read in conjunction with the appended drawings. For the purpose ofillustrating the invention, certain embodiments are shown in thedrawings. It should be understood, however, that the present inventionis not limited to the arrangements and instrumentality shown in theattached drawings.

DETAILED DESCRIPTION OF CERTAIN EXAMPLES

Although the following discloses example methods, systems, articles ofmanufacture, and apparatus including, among other components, softwareexecuted on hardware, it should be noted that such methods and apparatusare merely illustrative and should not be considered as limiting. Forexample, it is contemplated that any or all of these hardware andsoftware components could be embodied exclusively in hardware,exclusively in software, exclusively in firmware, or in any combinationof hardware, software, and/or firmware. Accordingly, while the followingdescribes example methods, systems, articles of manufacture, andapparatus, the examples provided are not the only way to implement suchmethods, systems, articles of manufacture, and apparatus.

When any of the appended claims are read to cover a purely softwareand/or firmware implementation, at least one of the elements in an atleast one example is hereby expressly defined to include a tangiblemedium such as a memory, DVD, CD, etc. storing the software and/orfirmware.

Radiology Information Systems (RIS) and other clinical informationsystems are in wide use in the healthcare industry to manage radiologydepartments in hospitals and independent radiology clinics. Thesesystems typically incorporate functionality to schedule patients onradiology equipment such as computed tomography (CT) and magneticresonance imaging (MRI) machines. However, radiology exams also requirea numbers of other resources such as technicians, nurses, radiologists,anesthesiologists and other equipment such as portable ultra sound andX-ray machines. In general, these resources are not scheduled and areassumed to be available during the times when the exams are scheduled.However, this is not always true and leads to delays in completing thescheduled exams. Certain examples provide one or more methodologies toschedule resources that are available for radiology exams to help ensurethat the exams can be performed as scheduled. Not all resources areneeded for the entire duration of the exam, so the resources arescheduled only for the parts of the exam for which they are needed.Moreover the exam duration varies based on a number of factors. Thesedurations are estimated by analyzing historical data so that exams canbe completed in allotted times with high probabilities. In addition,utilization of the resources is automatically analyzed to enable betterplanning at hospitals and clinics.

Exams to be performed can be divided into subtasks that are to beperformed consecutively based on resource requirements. Each subtaskrequires a different set of resources than those required by thesubtasks that precede and succeed it. The time that is needed for theentire exam and for each of the subtasks is estimated. The estimationcan be based on analysis of historical data on exam completion timesand/or knowledge of experts in the domain, for example.

Prior Radiology Information Systems (RIS) did not have a capability toperform multi-resource scheduling to ensure that all the resourcesrequired for performing an exam are available as needed during the exam.Without multi-resource scheduling, delays can be introduced incompleting the exams and resources are often under-utilized. Amulti-resource scheduling methodology can schedule all resources neededby an exam. The methodology is capable of performing both automatic andmanual scheduling, for example.

In some examples, availability of each resource involved in a task isobtained from a RIS and/or scheduling/calendar application (e.g.,Microsoft Outlook™ and/or other electronic calendar) of the resourcepersonnel. When a patient needs to be scheduled, the schedule/calendaris searched to find time slots where all required resources areavailable. The time slots are presented in increasing order ofdesirability to the scheduler. The scheduler selects a slot from thosepresented to schedule the exam. The patient and other medical personnelinvolved are then notified.

A scheduling algorithm drives the scheduling process. The problem offinding and ordering the available time slots can be formulated as aconstraint satisfaction problem. The goal is to ensure that allresources needed for the exam are available when needed. When multipleresources can perform a task, the best resource is selected based on anumber of user specified criteria. Existing constraint program solverscan solve this constraint satisfaction problem. Additionally, aheuristic algorithm has been developed to solve this problem bysystematically searching linearly in time to find open slots when allrequired resources for the exam are available, for example.

Certain embodiments provide systems and methods for systemicallyorganizing tasks and assets of a process to more effectively achieveimmediate and longer-term macro objectives. In certain embodiments,scheduled tasks are organized using, for example, a critical path method(CPM) and the tasks therein are exposed to durations which areprobabilistic and are either within the endogenous variation control ofthe system or are exogenous factors to which the system must be robustto. Measures of duration, availability and reliability to calculate anenumeration of scenarios in the context of variation is used todetermine the probabilities of meeting a selected schedule (schedulerisk). The probabilistic measures of duration, availability andreliability are functions of path dependent consumption and utilizationdecisions that are made to determine the use of the assets of theprocess. Using a multi-modality simulation methodology, for example, aprocess transfer function of the probabilistic measures may be derived.It is these estimates of duration, both endogenous and exogenous, thatare described by simulation that create the task durations and logic forinterdependencies which in turn are used to calculate schedule risk inthe CPM method. Certain embodiments provide decision support to helpmake effective decisions in real time or substantially real time whileembedded in a highly variable and interdependent process. These decisionsupport embodiments can be automated or prescriptive to the processstake-holder.

Certain embodiments provide systems and methods to manage changes to aschedule to accommodate changes that are internally or externallyinduced and do so in a way that reduces or minimizes overall healthdelivery system throughput or quality degradation. Certain embodimentsprovide systems and methods to review what has recently happened in aprocess, to view actual current process operations, and to view what ison the schedule looking forward into the near term future. Specificassets such as plant & equipment, people, physical location andinformation are exemplary entities being tracked and dynamicallymanaged.

Certain embodiments are adaptable and dynamically configurable such thatactivities can be rescheduled based upon, among other things, state(s)of patients, providers, and assets within a procedure and/or scheduledfor a procedure. Increased adaptability and dynamic configurability helpclinical systems and personnel to function more reliably and to berobust to exogenous forces outside of process control such as whatsymptoms patients present with, time of emergency, volume of patientmedical demand, and the like.

Certain embodiments include Duration Estimator, Block AllocationPlanner, Day View, Day Planner/Day Replay and Provider/Patient Kiosk aselements for information and decisioning designed to reduce systemicvariations by eliminating schedule risk up front and enabling rapidon-the-fly response to unanticipated perturbations to the clinicalprocess, for example.

Referring now to FIG. 1, a block diagram illustration of an examplesystem 100 for use in planning clinical procedures is provided. System100 includes a duration estimator module 110, block allocation plannermodule 120 and user interface 130 as described in detail above. Whileembodiments have been described with reference to a clinical setting, itis to be appreciated that other environments may also benefit fromsimilar methods and modules described herein.

In some examples, the duration estimator module 110 is configured tocharacterize average duration times and variations from average durationtimes for a given procedure or activity. The block allocation plannermodule 120 is configured to schedule procedures or activities inaccordance with characterized times from the duration estimator module.The user interface module 130 is configured to permit a user tovisualize variation, to visualize scheduling opportunities andconstraints and to view information output for use in schedulingprocedures and activities. Each component or module will be described ingreater detail below.

The Duration Estimator 110, which may be thought of as a ‘better rulerto measure with’, measures variation so that procedure times are moreaccurate and so that schedule risk is reduced.

The Block Allocation Planner 120 may be thought of as a “defragmenter”for reserving blocks of time. Much like a computer hard drivedefragmenter, it re-sorts the time slots and rooms to be available forthe booking of surgeries in such a way as to satisfy constraints anddepartmental objectives. It factors in preferences and availabilitiesand solves for the best departmental allocation of space and time andthrough the allocation, help achieve department policy objectives suchas case mix, outcomes, safety and to provide incentive for desiredbehaviors.

The user interface 130 to the disclosed schedule decision support mayinclude at least one of modules configured to permit a user to visualizevariation, to visualize scheduling opportunities and constraints andprovide output for use in scheduling procedures and activities, orcombinations thereof.

In accordance with an exemplary embodiment, the scheduling system 100 isconfigured to aid in initially scheduling activities and procedures andis configured to visualize scheduling opportunities and constraints andwill be referred to herein as “Day Planner”. Day Planner may be thoughtof as a manufacturing requisition planner, it enables the scheduling ofspecific activities and all interdependencies—with the added benefit ofsimulating forward many alternative plans and contingencies.

In accordance with an exemplary embodiment, the user interface to theschedule manager as the process is occurring is configured to indicateand display variation along with suggestions as to “do-what” and enable“what-if” and will be referred to herein as “Day View”. Day View may bethought of as a “radar” for the clinical process, it brings schedulewith other location and clinical information so that the staff can knowwhen schedule deviations are occurring, what the cause is, have a way tovisualize process interdependencies, have the ability to play out orsimulate alternative process decisions and ultimately get the processstakeholders constructively involved in proceeding forward in a mannerthat has their intellectual buy-in to the course.

A user interface module is configured to provide output for use indirecting procedures and activities and will be referred to herein as“Provider/Patient Kiosk”. Provider/Patient Kiosk may be thought of asworkflow, the kiosk is information gathering and output for the variousstakeholders in the clinical process. It gathers information that islater used to reduce variation and it interacts with the stakeholders inmediums that are natural extensions of their native environments. Theuser interface may include computer display and/or reports.

It is to be appreciated that the clinical process decision supportmethods can include one or more of the capabilities described above, aswell as any combination thereof

By having a procedure finish before the scheduled end time, potentialscheduling flexibility is lost for other issues that inevitably ariseduring the day such as staff availability, rooms and equipmentconstraints. Potential throughput capacity might also be impacted inthat, over the course of a day, one or more additional procedures couldbe inserted into the schedule if flexibility were provided.

A longer than anticipated procedure can have back up or delay otherdependent procedures for a particular patient either in the originaldepartment or cross departmentally. Additionally, the rooms and assetsthat were originally allocated are no longer as available, and,therefore, other patients and activities are negatively impacted. Theremay also be unscheduled overtime of staff or extra costs associated withturning around apparatus. New schedules must be made that impactreworking of staff planning as well as the potential for rework on casepreparation for following or interdependent procedures. The anticipatedand/or needed throughput capacity may also be impacted negatively. Thesechanges reduce operating flexibility and increase the anxiety of theclinical process stakeholders.

Certain embodiments provide a proactive application looking ahead atprocedure scheduling and duration to avoid delays by triggering anadvanced warning with sufficient time to respond in an event thatscheduled procedures will start or end before or after their scheduledtime. Certain embodiments provide recommendation regarding one or morespecific decision(s) or action(s) can be taken to add, drop or movespecific cases, task and assets, for example.

In certain embodiments, scheduling is provided that accounts foravailable personnel, available physical space, and available blocks oftime, for example. Certain embodiments account for variations associatedwith fluctuating demand and asset availability.

In certain embodiments, multiple criteria may be set for a schedulingprocess. Additionally, various risks associated with selected criteriamay be taken into account. Furthermore, rather than providing a singleschedule that is designed with average or generic or judgmental timebuffers to compensate for variation, certain embodiments enable aplurality of scheduling scenarios to be manually or dynamically enteredor simulated automatically to explore an available solution space andramifications on current and future activities. Certain embodimentsprovide suggested decisions calculated to help meet one or more static,dynamic or path-dependent configurable objectives.

In certain embodiments, a scheduler provides a capability to view asingle or multiple process metric, agent, and/or asset of the process aswell as a dynamic impact on interdependencies such that one or morecauses of variation in that process may be explicitly communicated andunderstood. Certain embodiments enable a dynamic view to process riskalong one or more dimensions in real time (or substantially real timewith some inherent system delay) or historically, for example.Additionally, certain embodiments may prompt an alarm, action and/orwarning if a certain process variable trips a threshold set point, forexample.

In certain embodiments, multiple simulation modalities are employedincluding a critical path method coupled to discrete event, agent, MonteCarlo and/or continuous simulation. Using this coupling, one or moreobjectives of the process may be assessed.

In certain embodiments, Day View or other user scheduler interfaceprovides features for historical review such as replaying a day or pastseveral days in order to extract from and discover process dynamics,training, and knowledge capture for future use as well as foradministrative activity cost(s), protocol verification and billing, forexample.

Utilization and asset consumption may be viewed to help understand astate of dynamic interdependencies between scheduling processes and tohelp determine which a schedule is likely to be met. If a determinationis made that a schedule is not likely to be met, data may be viewedand/or used to help identify what assets and interdependencies arecauses of schedule variance.

A future schedule view may be provided to calculate “what-if” scenariotesting to help understand schedule changes and effects of endogenousvariation, such as schedule adds or drops, resource availability,unforeseen delays or failures, etc. Future schedule extrapolation helpsto enable a higher process entitlement via better decisions thatdirectly and indirectly affect variation and throughput, wait times,stocks, capability and uses of assets in procedure and resourcescheduling.

Thus, certain embodiments provide scheduling of processes in highlydynamic environments where knowledge workers and service providers areintegral agents of the process, rather than providing singular ordiscrete schedules with an objective and buffers allocated by judgmentor heuristics alone.

Day View can estimate durations from a historical book or record ofbusiness. If no historical data exists, data from other relatedfacilities may be used, for example. In certain embodiments, users cansubscribe to services to receive or exchange data to aid in durationestimation and other calculation, for example. Additionally, access toother user data can allow comparison of procedure times betweenusers/institutions, for example. After duration estimation, blockallocation occurs. Then, interdependencies (e.g., one x-ray machineneeded in two rooms; people, surgeons, instruments, etc., needed inmultiple places/times; etc.) are planned into the schedule. Then, DayView monitors activity as the day progresses in order to add, dropand/or otherwise intervene in a schedule with automated adjustmentand/or decision support. Other input, such as electronic medical record(EMR) systems, healthcare information systems (HIS), status/monitoringsystems (e.g., radio frequency identification, RFID, patient callsystems, patient bed monitoring, clinical systems and etc), opticalrecognition for shape of instrument/operating room activity, devices(e.g., electrocardiogram (EKG), anesthesiology, etc.), interaction withother processes, manual observations, staffing/equipment availability,may feed into Day View for correlation with a schedule or protocol.

In certain embodiments, a determination of an initial view of a schedulemay be prefaced by a sequence of analytical work. Activity durations areutilized to schedule time within available limits. In an example, blocksof time are defined within which procedures may be booked for or bythose entitled to provide clinical service.

Responsible scheduling is considered to include an estimate of durationand a block of time allocation within which the procedure is consideredlikely to finish. While under-scheduling procedure time creates delaysin subsequent procedure starts, over-estimating and blocking time foravailable assets may create under-utilized capacity.

When average duration forecasts are used in a clinical environment, andeach room is considered unique outside the context of the staff's beforeand after tasks, chaos often results from concurrent demands. Utilizingprobability density functions of time for a given duration estimation ofa surgery is a foundation for calculating a schedule's risk and systemlevel performance or optimization, for example.

In an example, a probability density function (PDF) of time for aprocedure is calculated, typically from historical records of similarprocedures. The historical frequencies, in histogram form, for example,are normalized by one or more standard statistical techniques to createthe PDF with area=1. Certain embodiments record information includingactual procedure code(s), time(s), staff patient specifics and processenvironment, for example.

Certain embodiments facilitate dynamic, intelligent schedule changebased on changes in the actual stochastic and interdependent processesof care occurring in the hospital. This method requires forecastdurations of procedures arranged within a schedule along withinterdependencies of space, people, equipment, consumables andinformation. Actual process feedback is provided such as from aninformation system, RFID, optical recognition, telemetry, and/or variousother clinical systems. An explicit mapping of interdependencies inprocess assets and their related task probabilistic durations ofactivities can be coupled to the system's simulation capability forfinding feasible solutions.

Examples of events necessitating modification to the schedule includestaff and equipment unavailability, upstream or downstream processes notable to provide or receive patients, devices needed in the scheduledtasks not functioning, people and equipment not in planned location,inputs from clinical or administrative systems not adequate, patientbiomedical adequacy or health status not within specification, addedprocedures not in the schedule, and dropped procedures for any reason.The schedule can be modified by changing assumptions in the activitiesused to create the schedule or dynamically managed in the Day Viewsystem. The changes to assumptions can be manual or computer generatedto exploit feasible solutions.

In an environment involving many interdependencies, variation in anyinterdependent factor can propagate process disturbance. Certainembodiments help facilitate understanding and proactive management offactors that, if delayed or accelerated from plan, will likely increasethe probability of delay and preclude a process operating objective frombeing met. Relevant algorithms can be executed using methods and systemsdisclosed by Akbay and Alkemper known as Decision Execution System, viahard-coded computer logic, and/or via configuration of commercialExtract-Transform-Load and workflow tools, for example.

Key interdependencies can be identified around consumption andutilization of assets in a process. These interdependencies can becaptured, for example, using a critical path method (CPM) transferfunction technique. Critical paths are calculated using method known inthe area of management sciences. Critical path and process slack timesare made explicit via calculation and display, for example. A criticalpath can be calculated knowing the structure of interdependencies andstate of the assets in the process using one or more Gantt and CPMmethods, for example

Certain embodiments use simulation to explore potential feasiblesolutions. For example, four modalities of simulation are employed toforecast asset and resource utilization assumptions. These fourexemplary modalities are agent based simulation (AB), discrete eventsimulation (DE), continuous or system dynamic simulation (SD), and MonteCarlo simulation (MC). A critical path method (CPM) can also berepurposed in a simulation-based mode in that CPM is used to calculatecritical path, probabilities of completion, and availability andfeasibility of a solution.

In some examples, dynamic system context and interaction between avariety of simulation and forecast modalities are analyzed forscheduling purposes. Different simulation and forecast modalities can beutilized, for example. Critical path methods and forecast modalities canbe utilized, for example. Methods such as CPM, DE, AB, MC, and/orcontinuous, differential or system SD, can be used. Historicalobservations may be organized in the form of a histogram and transposedinto a probability density function and a cumulative probability densityfunction (PDF) for incorporation into the CPM logic and as assumptionfeedstock for the simulations, for example. Using a number of differentsimulation modalities concurrently to solve forward-looked aspects of aschedule can help determine what will happen during the day, forexample.

In some examples, methods and systems are differentiated from Gantt andProgram Evaluation and Review Techniques (PERTs) that replacedeterministic duration assumptions in CPM with task durationprobabilities. Certain examples not only draw from a static assumptionof a probability distribution function such as PERT or Gantt but alsoprovide duration probabilities from coupling to a simulation of thephysical environment. Thus the CPM or PERT method is enhanced with amost recent actual duration that is observed within the hospital's orother clinical environment's operations from protocols that are tied tothe specific care pathways for each patient and also an added precisionof dynamic forecasts of duration that result from incorporation ofprocess signals and activities on a dynamic basis into probabilityassumptions feeding CPM/PERT.

Beyond minute to minute, hourly, shift, daily, weekly, monthly, and/orother operational time constant within which tasks of a process arescheduled and work, there are typically additional process objectives tobe managed and traded against as well as throughput, inventory,operating expense and ability to fulfill. These objectives can includescheduling and scheduling risk management methods. These macroobjectives include budget, asset and staff investments, such as, forexample, capitalized equipment, consumable stock, physical plant,staffing levels, staff competence and recruited staff Having actualcapability, capacity, and cost structure allow more effective use ofasset and staff investments. An ability to attract more inputs into thesystem or adversely exclude entrants that the process system would notbe advantageously suited to serve may be provided in Day View. Certainembodiments provide an ability to create economic value addition or anability to meet financial targets, for example. A virtuous cycle thatcreates re-enforcing dynamics has dynamic counter forces and limits togrowth. Attracting more entrants into the system than the system cansustain with expected or required service levels results in staffburnout or poor process outcomes. Over investing in capability whosecost cannot be liquidated result in financial loss that may not besustainable. Served markets may not have sufficient volumes to sustainentrants into the process system built with an operating (and cost)structure that is designed for more (or different) volume. Certainembodiments allow process stakeholders to utilize both immediate processdecisioning and policy and strategic decisions in such a way as to makeinformed decisions with probabilistic trade-offs.

In certain examples, methods and systems are disclosed that useconstraint satisfaction techniques to schedule multiple resources tohelp ensure exams can be performed when and where they have beenscheduled. Not all resources may be needed for the entire duration of anexam. Therefore, disclosed systems and methods can schedule resourcesonly for the parts of the exam where they are needed. Systems andmethods can jointly manage the clinic-wide concurrent and temporaldemands on resources.

In some examples, a radiological multi-resource scheduler incorporatesan economic value calculation for underutilized (and/or a constraintrelease value for oversubscribed) assets; temporally dependentconstraints such as those associated with contrast agent protocolexecution; efficient routing decision support based upon amulti-resource schedule; use of forecast and forecast confidenceintervals at the time of inquiry and booking in a radiology info system;throughput limitation attribution analysis for radiological departments;and/or multi-clinic resource planning and real-time what-was, what-is,forecast and what-if analysis for throughput and resource utilizationboth in aggregate and temporal form, etc.

Exam task durations can vary based on a number of factors that areincorporated at the time of scheduling. These durations are estimatedfrom analyzing historical data so that exams can be completed inallotted times with high probabilities, building upon the art disclosedin U.S. Patent Application Publication No. 2009/0122618 (“UsingBiometrical Information for Scheduling”), incorporated by referenceherein in its entirety, which correlates the length of procedures with anumber of factors such as patient's weight and medical state and thenuses that information to reduce the duration forecast interval whenscheduling. U.S. Patent Application Publication No. 2009/0119126(“Method to view schedule interdependencies and provide proactiveclinical process decision support in Day View form”) is also hereinincorporated by reference in its entirety and manages throughput andscheduling risk.

FIG. 2 illustrates an example of patients scheduled by day in radiologydepartments. Patients are scheduled into available appointment timeblocks. It is appreciated by clinicians that, on average, there is slackor flexibility in these time slots such that either emergency cases canbe absorbed and the pre-scheduled ones can flex or the scheduled caseswill have over- and under-runs that will balance out at the end of ashift. A result is that patients wait and certain staff face unfeasibledemands on their time and attention. FIG. 2 depicts the paradigmdisclosed here-in, where the schedule is not fixed into set timeincrements but rather results from the interdependencies of resourceavailability, clinical tasks and task durations. Staff can be booked onseveral concurrent cases, yet at the task level the clinical workflow isarranged to allow feasibility by the disclosed system.

FIG. 3 depicts an example of clinical tasks and resources within ascheduled duration. Tasks consuming the same resource have a temporalinterdependency when there is mutual exclusivity. Certain examplesaccommodate temporal interdependencies by treating them as a constraintto help ensure resource availability at the task level upon a schedulerequest. Using a Gantt approach, deterministic durations are utilized.Certain examples use either a deterministic or probabilistic duration,setting as an objective the level of acceptable schedule risk versusidle capacity. Either or both system level throughput and economics areobjectives facilitated by certain example systems and/or methods.

FIG. 4 shows example clinical tasks and resources within a scheduledduration. Staff decision-making is facilitated with a view of tasks,resources, patients and their relationships. What-if scenarios for caseadditions, forecasted or actual duration changes and schedule changescan be assessed with visual constraint output in real time.

FIG. 5 illustrates an example of resource constraint and routing.Resources, such as staff, can be viewed with respect to time for thesummation of all assigned clinical tasks. A further improvementconsiders not only unfeasible multitasking but transport times as well.Further, in large or distributed clinical settings, a schedulingconstraint satisfaction algorithm can provide case scheduling tofacilitate optimal routing of people and assets.

FIG. 6 illustrates an example resource utilization analysis. Whether byshift or over a 24 hour day, clinical loading and balancing can beobtained by aggregating from the task level. Additionally, the economicsof shift coverage, labor overtime and asset quantity may be traded offagainst historical or theoretical cases.

Certain examples divide exams to be performed into subtasks that are tobe performed consecutively based on resource requirements. Each subtaskrequires a different set of resources required by the subtasks thatprecede and succeed it. The time that is needed for the entire exam andfor each of the subtasks is estimated. The estimation can be based onanalysis of historical data on exam completion times and/or knowledge ofthe experts in the domain.

Availability of each of the resources is obtained from a clinicalinformation system (e.g., a RIS) and/or a calendar/scheduling program(e.g., Microsoft Outlook™ and/or other electronic calendar)) of theresource personnel and assets. When a patient needs to be scheduled,disclosed methods and systems search to find all time slots where allrequired resources are available. Time slots are presented in theincreasing order of desirability to the scheduler. The scheduler selectsa slot from those presented to schedule the exam. The patient and othermedical personnel involved are then notified.

A problem of finding and ordering available time slots can be formulatedas a constraint satisfaction problem. An objective is to help ensurethat all resources needed for the exam are available when and whereneeded. When multiple resources can perform a task, the best resource isselected based on a number of user specified criteria. Existingconstraint program solvers can solve this constraint satisfactionproblem. A heuristic algorithm for solving this problem is disclosed asan alternate to the constraint-programming algorithm. The algorithminvolves systematically searching linearly in time to find open slotswhen all required resources for the exam are available.

The disclosed systems and methods improve radiological scheduling in anumber of ways. For example, systems and methods provide multi-resourcescheduling of patients, resources/equipment, and required staff fordefined durations. Multi-resource scheduling can take into accountlocation of resources considered in the schedule and performpre-scheduling and/or real-time scheduling, for example. Multi-resourcescheduling provides an ability to communicate with Microsoft Outlook™for scheduling, creating staff resource appointments, etc.

Certain examples provide a scheduler loaded with pre-scheduled exams.The scheduler uses resource historical information to calculate possibleareas of over and under resource utilization. The scheduler providesresource schedules for rooms, equipment, and staff at a glance. Viewscan be user configurable in real time, for example.

Communication with the scheduler's pre-scheduled exams can be used tocorrectly schedule new exams based on following criteria: schedulingalgorithms, a resource scheduling template, an exam template, an exam inresource template, patient conflicts, staff resources, etc. Schedulingalgorithms can operate based on one or more criteria/guidelines such asfirst available, horizontally fill rooms, etc. The resource schedulingtemplate can include one or more room open/closed templates based onpatient types, for example. The exam template can be used to schedule ornot schedule an exam based on patient type. The exam in resourcetemplate can be used to schedule or not schedule an exam into specificroom(s) based on patient type. Patient conflicts can include one or moreof preparation time, a previously performed and/or future scheduledprocedure with conflicting contrast, contrast fade time, similar examchecking, etc. Staff resources can include selecting a specific personbased on availability, generic resource, etc.

Certain examples provide scheduler resource optimization based onaffects of addition of emergency procedure(s) and/or affects oflengthier procedure duration. Staff can be alerted to reschedule.Patients can also be notified. Resources can be manipulated based on aresource's current schedule. Both room and equipment resources, as wellas staff resources, can be optimized and/or improved.

In certain examples, information for scheduling includes exam detail,staff resources, additional equipment/resources, etc. Exam detail caninclude performing resources, resource templates, exam templates, examin resource templates, duration of exam, exam protocol, contrastconflict, procedure preparation time, modality type, etc. Staffresources can include a specific duration for each staff resource (e.g.,for a select generic and/or specific resource). Staff resources can beintegrated with an electronic calendar/scheduling program to schedulebased on staff availability, for example. Additional equipment/resourcescan include a portable resource, a waiting and/or observation room,injection preparation room and/or time, etc.

Certain examples accommodate both initial scheduling and futurescheduling. For example, the referring provider's office calls toschedule an outpatient appointment. The appointment is visible bybrowser and/or integrated into the provider's system. In the example,the exam requires IV insertion prior to start of the exam in a preproom. The schedule incorporates clinical response time for contrastagents and ensures diagnostic imaging activity is within protocol. Theschedule also includes a patient duration in the prep room. Thescheduler also accommodates various staff resource(s) required for tasksas well as time in those task(s). The scheduler notes which resource(s)will be used in the exam and derives a total exam duration from taskforecast and temporal feasibility, for example. The scheduler determinesan exam completion risk evaluated by imposing a desired scheduleduration on the exam. The scheduler can also note whether a portableunit will be used partially in the exam. Post exam patient observationrequirements can also be incorporated into the schedule.

When scheduling an emergency examination, the scheduler notes theemergency procedure and conducts real time (or substantially real time)scheduling of the exam based on information regarding room, equipment,staff, etc. The scheduler may need to manipulate the present schedule toreallocate room, staff, resources, etc., so the scheduler provides auser with an ability to manually view room, staff, resources, etc.

Certain examples provide an ability to manually schedule the emergencyexam with correct resources. The scheduler depicts the new emergencyexam added to schedule and its impact on other activity and resources.The scheduler can help optimize the current resources based on additionof the emergency exam. The scheduler can alert a front desk (e.g.,patient tracking resource) to update patients about delays or reschedulepatients as appropriate, for example. Scheduler input/output can beprovided to hospital flow control such as GE Whole HospitalOptimization™

Certain examples illustrate a use case for scheduler optimization.Certain examples project optimal utilization of resourcesroom/equipment/staff based on historical data. The scheduler can displaystaff schedules including appointments entered in an electronic calendarprogram, for example.

In some examples, a radiology scheduling system enables efficient andcomprehensive use of diagnostic imaging while also achievingdepartmental level throughput and/or capacity to serve and economicobjectives. Procedures can be scheduled in advance and/or accommodatedon an ongoing and/or emergency basis. Users can include schedulers,clinicians performing the resultant workflow, and management analysts.

Efficient and comprehensive use of people and assets lowers the overallcost of radiological services, decreases the probability of clinicalerrors whose root cause is personnel or equipment overloading, decreasesthe occurrence of wasted procedures where radiological preparations andimaging were not executed per the medical protocol, and also helpsensure access to diagnostic imaging balanced by the constraints of staffand equipment availability and economics.

To achieve these objectives, the tasks of radiological services at theclinical workflow level and their interdependencies must be managedthrough time. Only reserving an asset such as a piece of diagnosticimaging equipment for a set block of time, as is the current art,ignores the realities that a given clinician may be required to be inmore than one location at the same time or that clinical workflows havetemporal constraints such as adequate time for contrast agents todiffuse, yet not expire. Multiple resource scheduling advances theprocess and outcomes of radiological services.

In certain examples, the multi-resource radiological scheduling systemsand methods disclosed here-in operate in two modes. In an analyticalmode, historical and/or theoretical cases, actual and/or proposedstaffing, and other resources are used, and a department is analyzedoff-line for improved operation opportunity assessment. In an operatingmode, the system schedules cases in advance of the actual clinicalactivities and then dynamically assists in the clinical workflowanalysis and control as those procedures are executed.

Certain examples improve scheduling with a capability to build scheduledurations from the task duration and temporal interdependencies uprather than simply allocating defined increments of time, such as in15-minute blocks. This is a significant advancement in the art ofscheduling and managing a radiological department because the concurrentscheduling of resources and the ability to dynamically manage protocolswith various levels of intensity over time, such as perfusion which hasa dosing, wait and imaging cycle that does not require uniform clinicalresource consumption. Previously, perfusion and imaging activities havebeen treated independently of each other and of other clinical activityin the radiology department. Certain examples overcome many protocolexecution defects by specifically managing the tasks of a given protocollongitudinally over time. The schedule, therefore, is a function ofresource availability, clinical tasks and task durations. Staff can bebooked on several concurrent cases, yet at the task level the clinicalworkflow is arranged to allow feasibility by the disclosed systemsand/or methods.

In addition to the temporal aspects of each resource, there is a spatialcomponent. The multiple resources needed for a procedure must beavailable where needed. Traditional methods to lower the impact of nothaving apparatus where there is a need to have them is to purchase moreassets rather than managing the workflow and location staging of mobileapparatus as the disclosed system does. The present systems and methodsconsider transport time in large clinics and in venues where distributedworkflow occurs, such as, for example where a perfusion is administeredto a hospital in-patient who is then transported to diagnostic imagingapparatus.

Routing decision support based upon the multi resource schedule isprovided. Though real time location information is not required, it mayadvantageously be employed in at least one example. OperationsResearchers, Management Scientists and Industrial Engineers are versedin a class of routing optimization algorithms typically referred to asTraveling Salesman solutions. Certain examples implement thesealgorithms in radiological scheduling and control. By the advantageousapplication of this art in radiology, routing decision support isprovided. With real time location information, certain examples estimatetransportation time and enables transport management. Further, in largeor distributed clinical settings, the scheduling constraint satisfactionalgorithm can provide case scheduling to facilitate optimal routing ofpeople and assets.

Certain disclosed systems and methods, because they are designed tomanage at the protocol task level, are advantageously able to comparewhat is required to be at a certain location and time per themulti-resource schedule to the actual availability of each of theresources. A status is provided to the clinicians when location data isavailable, such as, for example an RFID asset tracking system. Status ofpeople location can be obtained from their own calendar managementinfrastructure, provided that the activity and location refresh rate isfaster than the radiology department workflow task durations beingmanaged by disclosed systems and methods. Though improbable, the systemdoes consume outputs and provide inputs to calendar managementinfrastructures.

It can be appreciated that it is easier operationally to schedule amajor fixed asset, such as a MRI machine than to also schedule a seriesof workflows that consider where staff and ancillary assets such asportable ultrasound devices are. It is assumed that other resources willflex to the needs of a scheduled procedure on a large stationary asset.When this is not possible on an ongoing basis, staff or other resourcesare added to the radiology department.

As a radiology department becomes very busy (e.g., over 90 percentcapacity utilization), interactions between resources and physicallocations with the activities in a healthcare facility (e.g., ahospital, clinic, physician's office, etc.) can materially impactthroughput and the delivery of quality care. This is a result of theinterdependencies and randomness of the demands on shared resources, forexample. It can also be appreciated that while on average, a radiologydepartment may run at 75 to 85 percent of theoretical capacity; thereare multiple episodic excursions on a daily basis into the maximumutilization of staff or other shared resources. Observable symptoms ofthis dynamic can include late procedure starts, clinical errors such asimpartially executed and incorrect protocols, rework of imagining forlack of correct perfusion management, patient wait times, and staffanxiety, for example.

In some examples, systems and methods can operate based on work shift,12-hour, and/or 24-hour mode.

In some circumstances, the economics of a department may not allow theaddition of more resources to serve peak demands. However, due to thehidden cost of imaging rework and the need for flexible capacity toaccommodate exogenous demand created by emergency procedures such asstroke patients (who take precedence over scheduled procedures inradiology departments co-located at hospitals), it is highly desirableto be able to manage through excursions when the radiologicaldepartment's resources are in very high utilization.

Certain examples enable the calculation of capacity utilization givenstaff scheduling, physical assets, a patient demand and resultingprotocols. Further, certain example systems and/or methods, because oftheir specific management of radiology resources at the task level, cancalculate activity cost in addition to approximating the revenues fromthe case mix being superimposed onto the department.

Alternatively, given any limiting constraint or combination there-of ontheoretical capacity entitlement, certain systems and/or methods canestimate the opportunity costs of a constrained resource (e.g., staff,schedule of staff, diagnostic imaging equipment, ancillary equipment,physical plant, case mix and volume and various versions of a protocol,etc.).

Certain examples additionally calculate the temporal aspects ofconstraints. Examples include the identification of how many of certainprotocols can be executed under given demand scenarios, how long a queuewill build, by time of day, under various operating scenarios of theradiology department (emergency procedure add, staff leaving, equipmentdowntime), etc.

It can also be appreciated that a radiological department, especially aco-located or shared one with a hospital, does not operate withoutinterdependency on the clinical workflows of that hospital. Previously,simplifying operating modes were created to minimize the coordinationbetween hospital clinical activity and diagnostic imaging. An example ofsuch an operating mode is for the radiology department to take primarilyoutpatients in the morning and inpatients in the afternoon. The theorywas that outpatients must travel to the clinic while inpatients can ineffect be queued by staying in the hospital until the outpatient demandis satisfied.

One opportunity lost in such simplifying operating modes is at thesystem level. There is also a holding cost for inpatient bed occupancy.For example, the accumulated delay resulting from diagnostic imaging isoften sufficient to result in patients not being discharged when theyotherwise could have been. A result is lost capacity in the hospitalwith resultant additional reimbursements. Disclosed systems and/ormethods enable joint management of clinical activity whereas the priorart could not for its lack of ability to manage multiple resources atthe task level.

Beyond the coupling of a radiological department with a hospital, forexample, resources can be managed across a multitude of clinics that aregeographically separated such as within a city or region.

Disclosed systems and/or methods load and balance the workflow of aradiology department (or multi-site coordinated departments) byaggregating resource consumption as a function of time from the tasklevel. In an analytical mode, the binding constraints are calculated aswell as the slack values of relaxing those constraints. In an operatingmode, the system schedules and manages workflow to the department'sbinding constraint.

System(s) and/or method(s) can be deployed in an analytical and/oroperations mode. For example, in the analytical mode, scenarios ofactual patient demands or theoretical ones may be considered forwhat-was, what-is, forecast and what-if analysis for throughput andresource utilization both in aggregate and temporal form. In theoperational mode, the multi-resource scheduling system manages the tasksof radiological departments.

Because at least certain disclosed system(s) and/or method(s) scheduleat the task level and subsequently calculate the aggregate duration, andbecause the system(s) and/or method(s) facilitate estimation ofscheduled risk (a method of which is also disclosed in U.S. PatentApplication Publication No. 2009/0119126: Method to view scheduleinterdependencies and provide proactive clinical process decisionsupport in Day View form, which has been incorporated by referenceherein) to manage throughput and scheduling risk, it is thereforerequired that the task durations of the protocols being managed beinput.

Certain examples use either deterministic or probabilistic task durationfor radiological department scheduling and analysis. These durations areobtained a-priori from clinical experts, statistically characterizedhistorical data of the given radiology department, industry norms orpeer groups.

Users in operating mode are predominantly of two roles: those whoschedule radiological services in advance and the clinicians who areexecuting the protocols related to diagnostic imaging. Operations usersdo not typically have a comparatively long time to assess the state ofthe schedule and clinical activity as would an analyst using the systemin an off-line mode. Certain examples thus provide visual analytics inthe form of task detail, the status of tasks such as their relationshipto the critical path or being a binding constraint, location informationif available and the relationships of tasks to each other and to themultiple resources in the radiological department and beyond if soconfigured (for example, integrated into the flow control of a hospitaland/or real time location based infrastructure and other interdependentclinic's systems).

Users interface with certain example systems by active mouse draggingand dialog boxes that have intelligent, contextually relevant contentfrom which to select, for example.

Schedulers select a slot from those presented to schedule procedures.The patient and other medical personnel involved may then be notified inan example by typical components and infrastructure such as pagers,visual bed boards, PDAs, calendar systems and etc.

Referring to FIG. 2, a user is presented 200 with categories in tabularform 205 such as scheduler information, exam data, resourcerequirements, patient information and utilization. Highlightinginformation tabs subsequently displays contextually relevantinformation, an example being that of patient data. Example patientinformation includes an identification field 210 that is configurable todisplay a patient name or an anonymous representation of a uniqueindividual for privacy purposes, such as those required by HIPPA whenthe system is deployed in a manner that others than clinicians may viewthe screens. Relevant and configurable data such as procedure 220, starttime 230, duration 240, requisite or exception resources 250 andschedule 260 are available along with task aggregated proceduredurations.

In certain examples, disclosed methods and systems can operate in anumber of exemplary configurations. In one example, task durations thatresult from the execution of specific protocols and are interdependentupon resource availability are aggregated. An example task durationaggregation is depicted in FIG. 2 and will be further described withrespect to subsequent figures. Alternatively or in addition, setdurations, such as a block of time, can be imposed as is done in thecurrent scheduling art. Certain examples provide both durationapproaches as well as resultant task management and schedule riskcalculations.

Referring again to FIG. 2, a given patient's procedure is characterizedas having a starting time 261 and a forecasted completion time 262. Howthe tasks that are being managed to create the forecast will beenumerated in FIG. 3. It is notable that at a given time window 263,many procedures are concurrently being executed. As can be appreciated,there may be interdependencies there-in because the same clinicians maybe performing radiological services to multiple patients in this window.

The relation of a single procedure's clinical tasks within a scheduledduration are described in FIG. 3 as is a method to aggregate tasks toderive the total scheduled time and the mechanism/procedure by whichrequisite resources are reserved. A protocol 300 includes two tasks witha calculated duration of duration 305 that begins at time 261 and isforecasted to be complete at time 262. The temporal relationship is thattask 310 is performed first, followed by task 315. Tasks can be serialor parallel and the determination thereof is established by aradiological protocol. A serial relationship is depicted 300. Task 315is illustrated as beginning prior to the completion of task 310 by alength of time 320. This condition occurs when the duration 305 isspecified as being fixed or if the completion time 262 is after the endtime of task 310, for example.

In prior methods of radiological scheduling, tasks and their requisiteresources are not considered discretely. An example of a specifiedduration 305 is scheduling into a defined block of time such as one hourfrom 8 AM to 9 AM. The two tasks may be achievable in that duration ifresources are available when and where needed. However, if aninterdependent resource, such as a certain technician who is alsoservicing another patient, is not available for the present patient, atask such as 310 runs late. Disclosed system(s) and/or method(s)minimizes the probabilities of the same resources being a bindingconstraint when concurrent demands are made. Each task, 310 and 315specifies what resources are required in their execution.

Considering the exam's required resources within a scheduled duration,FIG. 4 depicts task and resource information 400 under the system'sexample embodiment Exam tab 220. A certain clinical protocol that isscheduled 405 requires two tasks that are specified a-prior as part ofthe radiological department's protocol conventions. Each task requirescertain resource types, also specified a-priori in the protocolconventions. The disclosed system facilitates the concurrent executionof many protocols and different conventions for those protocols. Thisfeature is enabled with a completely data-table driven relational logicand provides dialog boxes for specific configuration, such as, whatavailable resource is to be scheduled against a discrete task or generictask type or other operating heuristic particular to a givenradiological department. Additionally, an optimization algorithm canassign resources to tasks.

The procedure 405 specified two tasks, “Prep” and “Scan” whichsubsequently called resources. Returning to FIG. 3, procedure 405 ofduration 305 in length can be thought of as having task 310 as “Prep”and 315 as “Scan”. The “Prep” task 310 called the “Preparation Room” asa resource while “Scan” task 315 called resource “CT1” and a Technician,who in the example embodiment is “Mary”. Technician is an example of aresource type and Mary an assigned resource of that type who metconfigurable assignment heuristics, a user specified manual selection ora selection made by the optimization algorithm.

Resources 415 assigned to the tasks in protocol(s) of procedure 405 areconcurrently engaged in the execution of other procedures 410. Theexplicit scheduling assignment at the task and resource level aremanaged. The resultant clinical workflow being performed by a givenperson such as “Mary” to complete multiple tasks with several patientsis constructed to avoid mutually exclusive tasks at the time ofscheduling. Scheduling typically begins weeks, days and hours ahead ofthe actual clinical care as well as in real time when, for example, anemergency patient presents such as a person being assessed for stroke(when time is of the essence). A schedule that had been stabilized maytherefore be dynamically reconfigured for the new need and the workflowalong with timing of all radiological resources is instantaneously (orsubstantially instantaneously) calculated. Further, interdependenciessuch as transport and staff can be notified of a change before effortwould be wasted. Additionally, the temporally dependent protocolsimpacted, such as those with perfusion, can be dynamically rescheduledso as to minimize the likelihood that they will be lost, as is the oftenoccurrence with prior methods of radiological scheduling.

Referring to FIG. 5, resource constraints, such as concurrentactivities, schedules and spatial logistics, are managed. The schedulingdetail 500 is selectable 505 from the various other multi-resourcescheduling components 205. Specific resources 510 may be manuallyscheduled or assigned by algorithm. The resultant scheduling workflow,by time and duration for each resource is calculated. By aggregatingfrom task to resource, a determination can be made regarding whatradiological department availabilities exist or can exist withrescheduling. In the example depicted in FIG. 5, a number of resourceshave capacity at 6 PM 520. A new case or a case from earlier in the daythat was impacted by a change can include protocols that these availableresources can service. If so, a case is scheduled and resources arereserved, with their workflows thus updated. Resources and resourcetypes not available when a demand is present are considered as bindingconstraints that have an economic value proposition associated withthem.

In an off-line mode used for radiological department analyticalassessment, the pattern of economic and service capacity that isavailable or is lost is aggregated to provide the analyst with decisionsupport information to make clinic investment, staffing and service linerecommendations.

Returning to the management of task to task timing whose dual managementpurpose is to avoid delays for lack of a resource as well as to factorin transportation time, a window of time 515 is considered. Continuingwith prior example, the same resource 415 is scheduled for two tasks aspart of different procedures with different patients located indifferent areas. Should the spatial distance between those activities besuch that excessive time is lost (excessive being characterized by itsduration being sufficiently long that it unacceptably decreases theprobability of completing the requisite clinical task to which one istransporting to), then it is desirous to have sufficient time 320between tasks. In an example, the heuristic to reason if physical spaceresources associated with two adjacent tasks are sufficiently spatiallyseparated thus requiring time to move between them and that thetransport time relative to the task time decreases the task completionprobability below an adjustable level.

Managing the capacity of the multiple radiography resources is providedin certain examples. Referring to FIG. 6, resource utilization analysis600 is achieved in the example within a section focused on utilization605. Consider the resource CT1 601 being analyzed for daily working hour615 capacity utilization 620. It can be appreciated that the time scaleof analysis can be any time increment from minutes to hours, shifts,weeks, months and years for whatever part of the daily operating cycle.

Radiology multi-resource scheduling requires a tradeoff between theclinical throughput and its resulting services revenues and the cost ofhaving resources that create the capacity to serve. Certain examplesprovide an ability to assess service level and economics. Capacityutilization is an example of a metric that is calculated to provide theanalyst decision support. On an annual basis, a resource, on average mayhave utilization that is significantly below a daily or seasonal peak.The analyst can explore policy decisions such as staffing for peaks,modifying the schedule or coordinating with other radiology operations.It is also beneficially provided that underutilization of resources isidentified. The system's optimization algorithm in one example consumesthe capacity utilization and economic opportunity cost transferfunctions in its exploration for the most robust system set points andpolicy heuristics. The mathematical programming is well appreciated bythose familiar with the art of Operations Research. The disclosedmulti-resource scheduling system hosts the algorithm.

The problem of finding and ordering the available time slots can beformulated as a constraint satisfaction problem. Constraint programmingis a programming paradigm where relations between variables are statedin the form of constraints. The availability of various resources for aradiology exam to be scheduled can be described using mathematical andlogical constraints. Constraint program solvers can solve thisconstraint satisfaction problem to generate a list of all possible slotsavailable for the exam. These slots can then be sorted based on theirdesirability and presented to the user who is scheduling the exam. Aheuristic algorithm for solving this problem is disclosed as analternate to the constraint-programming method. The heuristic algorithm,depicted in FIG. 7, at 705, begins by determining all possible timeslots available on the main radiology equipment (CT, MR etc.) needed forthe patient exam within a desirable time window specified by the user.The set, S, of these time slots available on the radiology equipment arethen pruned in a systematic manner based on the availability of theother resources needed for conducting the exam. For each slot in the setS (710), a determination is made regarding whether all of the resources(715) needed for the exam are available at the right time for performingthe exam (720, 725). If any of the resources required is not available,at 735, the exam slot under consideration is deleted from the set, S. Inthis manner, at 730, each slot in the set is examined, and those thatare not feasible due to the unavailability of at least one of theresources are deleted. At 740, the resulting set of undeleted slots arethen sorted based on their desirability to the patient and/or theclinic.

Thus, certain examples search to find all time slots where all requiredresources are available. Time slots are presented in increasing order ofdesirability. The best resource is selected based on a number of userspecified criteria. Exam completion risk is evaluated by imposingdesired schedule duration, for example.

In certain examples, a user can manually schedule emergency exam withcorrect resources. The scheduler can depict a new emergency exam addedto a schedule and its impact on other activity and resources. Certainexamples optimize or improve the current resources based on the additionof the emergency exam. The scheduler can alert a front desk (e.g., apatient tracking resource) to update patients about delays or reschedulepatients as appropriate, for example.

Emergency situations where a patient exam needs to be scheduled at aspecified time regardless of availability of resources occur frequentlyespecially in radiology clinics in hospitals. Such exams are conductedby preempting or delaying already scheduled exams. The exams that aredisplaced by the emergency exam need to be rescheduled. In FIG. 8, a newmethodology for rescheduling such exams is described. The methodologybegins by generating a list of scheduled exams that are displaced by theemergency exams (805). The list is sorted in chronological order of theexam start time. This list is processed one exam at a time starting atthe top of the list (810). For each exam in the list, it is examined, at815, to determine if it can be rescheduled (820, 825). Exams to beperformed on inpatients can in general be rescheduled in a largefraction of the cases. Scheduled exams where the outpatient is not at orin transit to the clinic can also be rescheduled in a majority of thecases. Exam cases where the outpatient is already at the clinic or theinpatient exam needs to be completed by a certain time cannot berescheduled. Such exams are delayed and appropriate personnel and thepatient are informed. When an exam is rescheduled or delayed it canaffect a number of other scheduled exams, which then need to be delayedor re-scheduled (830). At 835, any such exams are added to the list L.At 840, the process is repeated until all exams in the list arerescheduled (845).

FIGS. 7 and 8 depict example flow diagrams representative of processesthat may be implemented using, for example, computer readableinstructions that may be used to facilitate multi-resource scheduling,review, and rescheduling. The example processes of FIGS. 7 and 8 may beperformed using a processor, a controller and/or any other suitableprocessing device. For example, the example processes of FIGS. 7 and 8may be implemented using coded instructions (e.g., computer readableinstructions) stored on a tangible computer readable medium such as aflash memory, a read-only memory (ROM), and/or a random-access memory(RAM). As used herein, the term tangible computer readable medium isexpressly defined to include any type of computer readable storage andto exclude propagating signals. Additionally or alternatively, theexample processes of FIGS. 7 and 8 may be implemented using codedinstructions (e.g., computer readable instructions) stored on anon-transitory computer readable medium such as a flash memory, aread-only memory (ROM), a random-access memory (RAM), a cache, or anyother storage media in which information is stored for any duration(e.g., for extended time periods, permanently, brief instances, fortemporarily buffering, and/or for caching of the information). As usedherein, the term non-transitory computer readable medium is expresslydefined to include any type of computer readable medium and to excludepropagating signals.

Alternatively, some or all of the example processes of FIGS. 7 and 8 maybe implemented using any combination(s) of application specificintegrated circuit(s) (ASIC(s)), programmable logic device(s) (PLD(s)),field programmable logic device(s) (FPLD(s)), discrete logic, hardware,firmware, etc. Also, some or all of the example processes of FIGS. 7 and8 may be implemented manually or as any combination(s) of any of theforegoing techniques, for example, any combination of firmware,software, discrete logic and/or hardware. Further, although the exampleprocesses of FIGS. 7 and 8 are described with reference to the flowdiagram of FIGS. 7 and 8, other methods of implementing the processes ofFIGS. 7 and 8 may be employed. For example, the order of execution ofthe blocks may be changed, and/or some of the blocks described may bechanged, eliminated, sub-divided, or combined. Additionally, any or allof the example processes of FIGS. 7 and 8 may be performed sequentiallyand/or in parallel by, for example, separate processing threads,processors, devices, discrete logic, circuits, etc.

FIG. 9 is a block diagram illustration of an example multi-resourcescheduling system 900 for use in planning clinical procedures in aclinical enterprise. The system 900 includes a scheduler engine 910, ascheduler interface 920, and a clinical system 930. The scheduler engine910 generates a schedule of tasks, as described above in associationwith FIGS. 1-8, based on task information, sub-task information, andresource information. Such information can be obtained from the clinicalsystem 930, such as RIS, calendar/practice management system, electronicmedical record (EMR) system, picture archiving and communication system(PACS), imaging system, and the like. Schedule information, such as acompleted schedule and/or options for task scheduling/rescheduling canbe presented to a user via the scheduler interface 920, as describedabove in association with FIGS. 1-8. Information regarding a scheduleand its constituent tasks, sub-tasks, and resources utilized (e.g.,staff, equipment, room, etc.) can be provided to the clinical system 930as well.

FIG. 10 is a schematic diagram of an example processor platform P100that can be used and/or programmed to implement the example systems andmethods described above. For example, the processor platform P100 can beimplemented by one or more general-purpose processors, processor cores,microcontrollers, etc. The processor platform P100 of the example ofFIG. 10 includes at least one general-purpose programmable processorP105. The processor P105 executes coded instructions P110 and/or P112present in main memory of the processor P105 (e.g., within a RAM P115and/or a ROM P120). The processor P105 may be any type of processingunit, such as a processor core, a processor and/or a microcontroller.The processor P105 may execute, among other things, the example processof FIGS. 7-8 to implement the example methods and apparatus describedherein.

The processor P105 is in communication with the main memory (including aROM P120 and/or the RAM P115) via a bus P125. The RAM P115 may beimplemented by dynamic random access memory (DRAM), synchronous dynamicrandom access memory (SDRAM), and/or any other type of RAM device, andROM may be implemented by flash memory and/or any other desired type ofmemory device. Access to the memory P115 and the memory P120 may becontrolled by a memory controller (not shown). The example memory P115may be used to implement the example databases described herein.

The processor platform P100 also includes an interface circuit P130. Theinterface circuit P130 may be implemented by any type of interfacestandard, such as an external memory interface, serial port,general-purpose input/output, etc. One or more input devices P135 andone or more output devices P140 are connected to the interface circuitP130. The input devices P135 may be used to, for example, receivepatient documents from a remote server and/or database. The exampleoutput devices P140 may be used to, for example, provide patientdocuments for review and/or storage at a remote server and/or database.

Thus, certain examples provide schedule adaptivity, prediction, anddisplay. Certain examples incorporate clinical department economics andthe economics of adding a case or appointment, for example. Certainexamples interact with hospital, clinic, and/or healthcare facility onboth in patient and out patient levels, which often occur at differenttimes of day. Certain examples provide multi-clinic resource planning,mass balance, etc. Certain examples use an IBM iLog Gantt schedulinginfrastructure for scheduling flexibility and prediction. Certainexamples allow a user to determine whether a new case can be fit into aschedule and how much must be moved/adjusted to fit in the case.Additionally, certain examples help a user evaluate the financial impactof fitting in a case at a location. Certain examples help a userevaluate availability at a first location and availability at a secondlocation to help determine whether and where a case should be routed andinserted into a schedule. Certain examples provide load balancing anddynamic schedule adjustment during a day.

Certain examples provide an economic value calculation for underutilizedand/or oversubscribed assets. Certain examples provide routing decisionsupport based upon a multi-resource schedule. Certain example useforecast and forecast confidence interval at a time of booking in aradiology information system and/or throughput limitation attributionanalysis for radiological departments, multi-clinic resource planning,etc.

Certain examples can also provide prioritization of cases by descriptiveattributes of presenting condition. “Stat” indicators on add-inscheduling requests can also be prioritized. Certain examples provide anability for staff to provide feedback on actual “stat” request vs.actual presenting attributes and the creation of a credibility score. Incertain examples, cases can be prioritized by descriptive attributes ofability to pay. An authorization likelihood can be calculated based uponprogression of the workflow as a function of time and providedinformation, for example. Cases can be prioritized based upon fidelityof requisite preauthorization requirements met, for example.

In certain examples, global department objective function can bedetermined along the one or several dimensions of throughput, inventory,operating expense, ability to serve, financial risk and return, staffpreferences, staff “burnout”, etc. Routing decision support can beprovided based upon a multi-resource schedule. In certain examples, RFIDinformation can be used in supplying information to asset utilizationassumptions—historical durations, current location, anticipatedtransport time, etc. In certain examples, use of computer vision cansupply clinical workflow status and assumptions. Historical durationscan be used to inform a scheduler at a time of case booking, forexample. In some examples, scheduling input can be provided to hospitallocation tracking and bed board system. When faced with an infeasiblethroughput, certain examples can provide decision support on patients tomove, cancel, change or suggest to change procedures, etc.

Certain examples provide spatial-temporal visualization of scheduledclinical workflow. Certain examples provide spatial-temporalvisualization of actual clinical workflow. Certain examples enablevisualization of actual versus scheduled workflow.

Certain examples provide an ability to consume an ordered workflow orprotocol, such as from a medical society, standard operating procedure,or a doctor preference, and translate into schedule requirements.Certain examples allow simultaneous scheduling of multiple radiologyequipment and staff resources. Certain examples allow staff resourcescheduling for specific durations during procedures. Certain examplesmonitor equipment and staff resources and can dynamically changeequipment and staff resources in real time (or substantially real time).Certain examples project resource utilization for future equipmentand/or resource additions.

Certain embodiments contemplate methods, systems and computer programproducts on any machine-readable media to implement functionalitydescribed above. Certain embodiments may be implemented using anexisting computer processor, or by a special purpose computer processorincorporated for this or another purpose or by a hardwired and/orfirmware system, for example.

One or more of the components of the systems and/or steps of the methodsdescribed above may be implemented alone or in combination in hardware,firmware, and/or as a set of instructions in software, for example.Certain embodiments may be provided as a set of instructions residing ona computer-readable medium, such as a memory, hard disk, DVD, or CD, forexecution on a general purpose computer or other processing device.Certain example embodiments of the present invention can omit one ormore of the method steps and/or perform the steps in a different orderthan the order listed. For example, some steps may not be performed incertain embodiments of the present invention. As a further example,certain steps may be performed in a different temporal order, includingsimultaneously, than listed above.

Certain embodiments include computer-readable media for carrying orhaving computer-executable instructions or data structures storedthereon. Such computer-readable media may be any available media thatmay be accessed by a general purpose or special purpose computer orother machine with a processor. By way of example, suchcomputer-readable media may include RAM, ROM, PROM, EPROM, EEPROM,Flash, CD-ROM or other optical disk storage, magnetic disk storage orother magnetic storage devices, or any other medium which can be used tocarry or store desired program code in the form of computer-executableinstructions or data structures and which can be accessed by a generalpurpose or special purpose computer or other machine with a processor.Combinations of the above are also included within the scope ofcomputer-readable media. Computer-executable instructions include, forexample, instructions and data which cause a general purpose computer,special purpose computer, or special purpose processing machines toperform a certain function or group of functions.

Generally, computer-executable instructions include routines, programs,objects, components, data structures, etc., that perform particulartasks or implement particular abstract data types. Computer-executableinstructions, associated data structures, and program modules representexamples of program code for executing steps of certain methods andsystems disclosed herein. The particular sequence of such executableinstructions or associated data structures represent examples ofcorresponding acts for implementing the functions described in suchsteps.

Examples can be practiced in a networked environment using logicalconnections to one or more remote computers having processors. Logicalconnections may include a local area network (LAN) and a wide areanetwork (WAN) that are presented here by way of example and notlimitation. Such networking environments are commonplace in office-wideor enterprise-wide computer networks, intranets and the Internet and mayuse a wide variety of different communication protocols. Those skilledin the art will appreciate that such network computing environments willtypically encompass many types of computer system configurations,including personal computers, hand-held devices, multi-processorsystems, microprocessor-based or programmable consumer electronics,network PCs, minicomputers, mainframe computers, and the like. Examplescan also be practiced in distributed computing environments where tasksare performed by local and remote processing devices that are linked(either by hardwired links, wireless links, or by a combination ofhardwired or wireless links) through a communications network. In adistributed computing environment, program modules may be located inboth local and remote memory storage devices.

An exemplary system for implementing the overall system or portions ofexample embodiments of the invention might include a general purposecomputing device in the form of a computer, including a processing unit,a system memory, and a system bus that couples various system componentsincluding the system memory to the processing unit. The system memorymay include read only memory (ROM) and random access memory (RAM). Thecomputer may also include a magnetic hard disk drive for reading fromand writing to a magnetic hard disk, a magnetic disk drive for readingfrom or writing to a removable magnetic disk, and an optical disk drivefor reading from or writing to a removable optical disk such as a CD ROMor other optical media. The drives and their associatedcomputer-readable media provide nonvolatile storage ofcomputer-executable instructions, data structures, program modules andother data for the computer.

While the invention has been described with reference to certainembodiments, it will be understood by those skilled in the art thatvarious changes may be made and equivalents may be substituted withoutdeparting from the scope of the invention. In addition, manymodifications may be made to adapt a particular situation or material tothe teachings of the invention without departing from its scope.Therefore, it is intended that the invention not be limited to theparticular embodiment disclosed.

1. A multi-resource scheduler system for a clinical enterprisecomprising: a processor connected to a memory, wherein the processor isprogrammed to implement the system comprising: a scheduler engine togenerate a schedule for a clinical facility involving multiple tasks andusing multiple resources, the scheduler engine to identify a slot for atask defined by a scheduled task duration and one or more resources, thetask including a plurality of sub-tasks, each sub-task having a sub-taskduration utilizing one or more of the one or more resources, eachsub-task to be performed consecutively based on resource constraints,wherein the scheduler engine is to identify and select a time slot forthe task based on resource availability, the plurality of sub-tasks inthe task, and a duration associated with each sub-task, wherein resourceavailability information is obtained from a clinical information system,and wherein each resource is scheduled only for one or more sub-tasks inwhich the resource is involved; and a scheduler interface to display andfacilitate access to the schedule including the task and the pluralityof sub-tasks.
 2. The system of claim 1, wherein the scheduler engine isto identify and order available time slots for the task by formulatingand solving a constraint satisfaction problem based on the task, theplurality of sub-tasks, and the one or more resources used for eachsub-task.
 3. The system of claim 1, wherein the time to complete each ofthe sub-tasks and the task is estimated based on an analysis ofhistorical task and sub-task data.
 4. The system of claim 1, whereinavailable time slots are presented by the scheduler engine in order ofincreasing desirability to a user via the scheduler interface.
 5. Thesystem of claim 1, wherein when multiple resources can be used toperform a sub-task, the resource is selected based on a one or moreuser-specified criteria.
 6. The system of claim 1, wherein routingdecision support for the resources involved in the sub-tasks of the taskis provided based on the schedule via a routing optimization algorithm.7. The system of claim 1, wherein the scheduler engine is to rescheduleone or more tasks to include an emergency task by: determining a list oftasks displaced by the emergency task; selecting a first task from thelist of tasks, the first task including a plurality of sub-tasks;evaluating whether the first task can be rescheduled based on a patientcondition associated with the first task and resources associated withthe plurality of sub-tasks; determining an effect of rescheduling thefirst task on a second task; and rescheduling the first task toaccommodate the emergency task based on evaluating whether the firsttask can be rescheduled and determining an effect of rescheduling thefirst task.
 8. The system of claim 1, wherein the scheduler engine is toaccount for resource location when identifying and selecting a timeslot.
 9. The system of claim 1, wherein the scheduler engine is to usehistorical resource information to calculate one or more possible areasof over or under resource utilization based on a calendar ofpre-scheduled tasks and schedule new exams based on the calculation ofone or more possible areas of over or under resource utilization. 10.The system of claim 1, wherein the scheduler engine is to receiveresource availability information for a resource from a tracking deviceassociated with the resource.
 11. A tangible computer-readable storagemedium including a set of instructions for execution on a computer, theset of instructions, when executed, implementing a multi-resourceclinical scheduler comprising: a scheduler engine to generate a schedulefor a clinical facility involving multiple tasks and using multipleresources, the scheduler engine to identify a slot for a task defined bya scheduled task duration and one or more resources, the task includinga plurality of sub-tasks, each sub-task having a sub-task durationutilizing one or more of the one or more resources, each sub-task to beperformed consecutively based on resource constraints, wherein thescheduler engine is to identify and select a time slot for the taskbased on resource availability, the plurality of sub-tasks in the task,and a duration associated with each sub-task, wherein resourceavailability information is obtained from a clinical information system,and wherein each resource is scheduled only for one or more sub-tasks inwhich the resource is involved; and a scheduler interface to display andfacilitate access to the schedule including the task and the pluralityof sub-tasks.
 12. The tangible computer-readable storage medium of claim11, wherein the scheduler engine is to identify and order available timeslots for the task by formulating and solving a constraint satisfactionproblem based on the task, the plurality of sub-tasks, and the one ormore resources used for each sub-task.
 13. The tangiblecomputer-readable storage medium of claim 11, wherein the time tocomplete each of the sub-tasks and the task is estimated based on ananalysis of historical task and sub-task data.
 14. The tangiblecomputer-readable storage medium of claim 11, wherein available timeslots are presented by the scheduler engine in order of increasingdesirability to a user via the scheduler interface.
 15. The tangiblecomputer-readable storage medium of claim 11, wherein when multipleresources can be used to perform a sub-task, the resource is selectedbased on a one or more user-specified criteria.
 16. The tangiblecomputer-readable storage medium of claim 11, wherein routing decisionsupport for the resources involved in the sub-tasks of the task isprovided based on the schedule via a routing optimization algorithm. 17.The tangible computer-readable storage medium of claim 11, wherein thescheduler engine is to reschedule one or more tasks to include anemergency task by: determining a list of tasks displaced by theemergency task; selecting a first task from the list of tasks, the firsttask including a plurality of sub-tasks; evaluating whether the firsttask can be rescheduled based on a patient condition associated with thefirst task and resources associated with the plurality of sub-tasks;determining an effect of rescheduling the first task on a second task;and rescheduling the first task to accommodate the emergency task basedon evaluating whether the first task can be rescheduled and determiningan effect of rescheduling the first task.
 18. The tangiblecomputer-readable storage medium of claim 11, wherein the schedulerengine is to account for resource location when identifying andselecting a time slot.
 19. The tangible computer-readable storage mediumof claim 11, wherein the scheduler engine is to use historical resourceinformation to calculate one or more possible areas of over or underresource utilization based on a calendar of pre-scheduled tasks andschedule new exams based on the calculation of one or more possibleareas of over or under resource utilization.
 20. The tangiblecomputer-readable storage medium of claim 11, wherein the schedulerengine is to receive resource availability information for a resourcefrom a tracking device associated with the resource.
 21. Acomputer-implemented method for scheduling of clinical tasks involvingmultiple sub-tasks and multiple resources in a clinical enterprise, themethod comprising: identifying, using a processor, a slot for a taskdefined by a task duration and one or more resources, the task includinga plurality of sub-tasks, each sub-task having a sub-task durationutilizing one or more of the one or more resources, wherein eachsub-task to be performed consecutively based on resource constraints,selecting, using the processor, a time slot for the task based onresource availability, the plurality of sub-tasks in the task, and aduration associated with each sub-task, wherein resource availabilityinformation is obtained from a clinical information system, and whereineach resource is scheduled only for one or more sub-tasks in which theresource is involved; displaying the schedule including the task and theplurality of sub-tasks; and facilitating access to view and modify theschedule.
 22. The method of claim 21, further comprising reschedulingone or more tasks to include an emergency task, rescheduling comprising:determining a list of tasks displaced by the emergency task; selecting afirst task from the list of tasks, the first task including a pluralityof sub-tasks; evaluating, using the processor, whether the first taskcan be rescheduled based on a patient condition associated with thefirst task and resources associated with the plurality of sub-tasks;determining, using the processor, an effect of rescheduling the firsttask on a second task; and rescheduling the first task to accommodatethe emergency task based on evaluating whether the first task can berescheduled and determining an effect of rescheduling the first task.